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Handling fuzzy gaps in sequential patterns: Application to health

Sandra Bringay, Anne Laurent, Beatrice Orsetti, Paola Salle, Maguelonne Teisseire
2009 2009 IEEE International Conference on Fuzzy Systems  
Dealing with numerical data for mining novel knowledge is a non trivial task that has received much attention in the last years.  ...  We thus consider here fuzzy rankings based on a fuzzy partition provided by the experts. Rules can then better characterize how genes are correlated.  ...  CONCLUSION In this paper, we study the problem of mining biological data for discovering relevant gene interactions in the framework of breast cancer.  ... 
doi:10.1109/fuzzy.2009.5277107 dblp:conf/fuzzIEEE/BringayLOST09 fatcat:znpkocqys5gl3jkltz73xxi2ce

A novel anomaly detection algorithm for sensor data under uncertainty

Raihan Ul Islam, Mohammad Shahadat Hossain, Karl Andersson
2016 Soft Computing - A Fusion of Foundations, Methodologies and Applications  
Therefore, in this paper we propose a new belief-rule-based association rule (BRBAR) with the ability to handle the various types of uncertainties as mentioned.The reliability of this novel algorithm has  ...  and cancer cell data.  ...  , and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.  ... 
doi:10.1007/s00500-016-2425-2 fatcat:q7w3axww7jgcziuw6fv4kuploq

Proportion frequency occurrence count with bat algorithm (FOCBA) for rule optimization and mining of proportion equivalence fuzzy constraint class association rules (PEFCARs)

R Ramesh
2018 Periodicals of Engineering and Natural Sciences (PEN)  
To solve this problem this paper proposes a Proportion of Constraint Class Estimation (PPCE) algorithm for mining Enhanced Proportion Equivalence Fuzzy Constraint Class Association Rules (EPEFCARs) in  ...  However, a major weakness of FCARs Miner is that when the number of constrained rules in a given class dominates the total constrained rules; its performance becomes slower than the normal method.  ...  Next, it could directly find the position pos of certain nodes without considering the fuzzy support. The fuzzy confidence of a candidate rule is identified dependent upon this information.  ... 
doi:10.21533/pen.v6i1.278 fatcat:qtu7v3covjdtpdp4gkm53buzwm

Modern Applications and Challenges for Rare Itemset Mining

Sadeq Darrab, Databases and Software Engineering Group of Gunter Saake, University of Magdeburg, Magdeburg, Germany, David Broneske, Gunter Saake
2021 International Journal of Machine Learning and Computing  
Frequent itemset mining is the fundamental task of data mining that aims at discovering interesting itemsets that frequently appear together in a dataset.  ...  Then, we highlight the state-of-art methods for rare itemsets mining.  ...  Although a lot of efforts have been made to cope with the high amount of data for mining frequent itemsets, significant challenges still remain to detect rare itemset mining from big data.  ... 
doi:10.18178/ijmlc.2021.11.3.1037 fatcat:saxhq6lidrhojbqewysxiz7cfq

Predictive Analysis for the Diagnosis of Coronary Artery Disease using Association Rule Mining

Chetna Yadav, Shrikant Lade, Manish K Suman
2014 International Journal of Computer Applications  
In this paper, we present an improved association rule mining of data mining for the detection of Coronary Artery Disease (CAD).  ...  The whole concept behind the research is carried out by using a heart disease database, which is collected from different locations and from different patients.  ...  This work can further pave way for detection of cancer and other diseases and consequently impact the way such diseases are diagnosed.  ... 
doi:10.5120/15195-3575 fatcat:ot6ifq7epfhrdgdgykjqcqxcii

A fuzzy ART2 model for finding association rules in medical data

Yo-Ping Huang, Vu Thi Thanh Hoa, Jung-Shian Jau, Frode Eika Sandnes
2010 International Conference on Fuzzy Systems  
The proposed data mining procedure consists of two modules.  ...  The other module employs fuzzy set theory to extract fuzzy association rules for each homogeneous cluster of data records. In addition, an example is given to illustrate this model.  ...  In this paper, one case study is presented involving the grouping of patients who have undergone surgery for breast cancer.  ... 
doi:10.1109/fuzzy.2010.5584780 dblp:conf/fuzzIEEE/HuangHJS10 fatcat:atlzohaurnco3f3tcjf45yqzea

Frequent Pattern Retrieval on Data Streams by using Sliding Window

P. Kumar, P. Rao
2021 EAI Endorsed Transactions on Energy Web  
In this paper, the Frequent Pattern Retrieval strategy is planned by utilizing an FP tree approach and a sliding window model to extract noteworthy examples from data streams.  ...  The proposed technique accomplished less runtime with low memory use for the Breast disease dataset and different datasets to run the least utility edge contrasted with different existing procedures.  ...  For instance, breast cancer data is presented in the Brest Cancer Wisconsin dataset, where the information about heart disease is obtained in the Heart Cleveland dataset.  ... 
doi:10.4108/eai.13-1-2021.168091 fatcat:ud3pbbgmq5gl3b525spburyl7i

On the discovery of association rules by means of evolutionary algorithms

María J. del Jesus, José A. Gámez, Pedro González, José M. Puerta
2011 Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery  
The use of fuzzy rules in the evolutionary algorithms for association rule learning is also described.  ...  Association rule learning is a data mining task that tries to discover interesting relations between variables in large databases.  ...  Kwasnicka and Switalski 35 analyzed two medical data sets (Sutek-breast cancer and Szyjka-cancer of the cervix/ uterus) by using ARs.  ... 
doi:10.1002/widm.18 fatcat:hblu7qeye5ac3it5f3n6yma7wa

Fuzzy Frequent Pattern Mining Algorithm Based on Weighted Sliding Window and Type-2 Fuzzy Sets over Medical Data Stream

Jing Chen, Peng Li, Weiqing Fang, Ning Zhou, Yue Yin, Hui Zheng, He Xu, Ruchuan Wang, Arun K. Sangaiah
2021 Wireless Communications and Mobile Computing  
Therefore, this paper proposes a new weighted sliding window fuzzy frequent pattern mining algorithm based on interval type-2 fuzzy set theory over data stream (WSWFFP-T2) with a single scan based on the  ...  The weighted fuzzy frequent pattern tree based on type-2 fuzzy set theory (WFFPT2-tree) and fuzzy-list sorted structure (FLSS) is designed to mine the fuzzy frequent patterns (FFPs) over the medical data  ...  Zhu, “Fast algorithms for frequent itemset The Wisconsin Prognostic Breast Cancer Database (breast.- mining using FP-trees,” IEEE Transactions on Knowledge cancer.arff data) is used to support  ... 
doi:10.1155/2021/6662254 fatcat:3epihvfkwjeqneb2ttxsw275oy

Analytical Study of Association Rule Mining Methods in Data Mining

Bhavesh M. Patel, Vishal H. Bhemwala, Dr. Ashok R. Patel
2018 International Journal of Scientific Research in Computer Science Engineering and Information Technology  
In data processing, the foremost common and effective technique is to spot frequent pattern victimization association rule mining.  ...  There are such a large amount of algorithms that provides simple and effective method of association rule mining, however still some analysis is required which might improve potency of association rule  ...  They proposed an algorithm called Fuzzy-T ARM to classify the breast cancer dataset. Hybrid PSO/ACO Algorithm (PSO/ACO-AR).In Proc of ACIT2008, 2008.[7].  ... 
doi:10.32628/cseit1833244 fatcat:ndopsdk6enfr7hphvuhmiym43e

Special issue on soft computing and intelligent systems: Tools, techniques and applications

Sabu M. Thampi, El-Sayed M. El-Alfy, Sabu M. Thampi, El-Sayed M. El-Alfy
2017 Journal of Intelligent & Fuzzy Systems  
In [3], a novel method is proposed for early detection and diagnosis of breast cancer in digital mammograms.  ...  These papers have been reviewed and accepted for presentation at the symposium and for publication in the Journal of Intelligent & Fuzzy Systems (JIFS).  ...  In [3] , a novel method is proposed for early detection and diagnosis of breast cancer in digital mammograms.  ... 
doi:10.3233/jifs-169221 fatcat:f43kb5ygbfhlho5cfwogbcyegq

ICCUBEA 2019 Table of Contents

2019 2019 5th International Conference On Computing, Communication, Control And Automation (ICCUBEA)  
Paper Title 128 Review of Microwave based Imaging for Early Detection of Breast Cancer & a proposed architecture 129 Image based Product Recommendations using Market Basket Analysis 130 The Camouflage  ...  of Document with J48 Multi-Class Classifiers 101 Parallel Processing of Frequent Itemset Based on MapReduce Programming Model 102 Systematic Review of Data Mining based Recommendation Methods Reference  ... 
doi:10.1109/iccubea47591.2019.9128707 fatcat:3s3o5v2x3nepxeftk4jd64hjnq

Coverage-Based Classification Using Association Rule Mining

Jamolbek Mattiev, Branko Kavsek
2020 Applied Sciences  
Building accurate and compact classifiers in real-world applications is one of the crucial tasks in data mining nowadays.  ...  More precisely, we propose a new associative classifier that selects "strong" class association rules based on overall coverage of the learning set.  ...  Jamolbek Mattiev is also funded for his Ph.D. by the "El-Yurt-Umidi" foundation under the Cabinet of Ministers of the Republic of Uzbekistan.  ... 
doi:10.3390/app10207013 fatcat:c2zayoyd7bdrzbiqan3azeic4i

Big data analytics for preventive medicine

Muhammad Imran Razzak, Muhammad Imran, Guandong Xu
2019 Neural computing & applications (Print)  
We summarize state-of-the-art data analytics algorithms used for classification of disease, clustering (unusually high incidence of a particular disease), anomalies detection (detection of disease) and  ...  The aim of this study is to provide a comprehensive and structured overview of extensive research on the advancement of data analytics methods for disease prevention.  ...  Breast cancer wisconsin diagnostic (WDBC) Features of the breast cancer dataset are computed from digitized breast mass images of a fine needle aspirate (FNA) describing the characteristics of the cell  ... 
doi:10.1007/s00521-019-04095-y pmid:32205918 pmcid:PMC7088441 fatcat:x52upnuwbjdchkyb7hog5pvawm

Clustering Algorithm for a Healthcare Dataset Using Silhouette Score Value

Godwin Ogbuabor, Ugwoke F. N
2018 International Journal of Computer Science & Information Technology (IJCSIT)  
The huge amount of healthcare data, coupled with the need for data analysis tools has made data mining interesting research areas.  ...  Presently, a large number of clustering algorithms are available for clustering healthcare data, but it is very difficult for people with little knowledge of data mining to choose suitable clustering algorithms  ...  Maximal Frequent Itemset Algorithm (MAFIA) was used for mining maximal frequent patterns in the heart disease database.  ... 
doi:10.5121/ijcsit.2018.10203 fatcat:r5iimattufdsnd6qjtfi6eq7nm
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